Activity budget and gut microbiota stability and flexibility across reproductive states in wild capuchin monkeys in a seasonal biome
Bibliographic record
Abstract
ABSTRACT Energy demands associated with pregnancy and lactation are significant forces in mammalian evolution. To mitigate increased energy costs associated with reproduction, female mammals have evolved behavioural and physiological responses. Some species alter activity to conserve energy during pregnancy and lactation, while others experience changes in metabolism and fat deposition. Restructuring of gut microbiota with shifting reproductive states may also help females increase energy harvest from foods, especially during pregnancy. Here, we combine life history data with >13,000 behavioural scans and >300 fecal samples collected longitudinally across multiple years from 33 white-faced capuchin monkey females to examine the relationships among behaviour, gut microbiota composition, and reproductive state. We used 16S-based amplicon sequencing and the DADA2 pipeline to analyze microbial diversity and putative functions. Reproductive state explained some variation in activity, but overall resting and foraging behaviours were relatively stable across the reproductive cycle. We found evidence for increases in biotin synthesis pathways among microbes in lactating females, and that relatoe abundance of major phyla among the states was small but significant. Otherwise, gut microbiota structure and estimated functions were not substantially different among reproductive states. These data contribute to a broader understanding of plasticity in response to physiological shifts associated with mammalian reproduction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".